Determinants of asthma-related emergency department return visits in adults: A population-based study
Bibliographic record
Abstract
RATIONALE: Emergency department (ED) return-visit rates provide a measure of the quality of acute asthma care.OBJECTIVES: We sought to assess the impact of patient and site characteristics, including asthma management strategies, on return visits within 72 hours, prior to implementation of a standardized adult ED asthma care pathway in EDs throughout Ontario, Canada.METHODS: This population-based cohort study utilized comprehensive administrative health data from the Institute for Clinical Evaluative Sciences for adults 20 to 64 years old who had at least one ED visit for asthma from April 1, 2006 to March 31, 2008. Detailed information on ED management strategies was available on a subset of 37 sites whose staff attended pathway implementation workshops.MEASUREMENTS AND MAIN RESULTS: A total of 41,140 asthma visits to 167 EDs were analyzed. Most patients (64.8%) were triaged as high acuity and the majority (92.8%) were discharged. The return-visit rate was 2.8%. Female gender, younger age, higher acuity, leaving the ED before visit completion and prior admission or ED visit for asthma were associated with increased odds of a return visit. The only management strategy associated with reduced ED visits was access to 24-hour peak flow measurement.CONCLUSION: This study identified well-recognized patient- and hospital-level risk factors for return ED visits. Access to peak flow monitoring was the only protective management strategy found. As many ED asthma service and care gaps exist, province-wide implementation of a standardized care pathway may greatly impact ED management and improve patient outcomes including return ED visits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".